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Funk A, Florin TA, Kuppermann N, Finkelstein Y, Kazakoff A, Baldovsky M, Tancredi DJ, Breslin K, Bergmann KR, Gardiner M, Pruitt CM, Liu DR, Neuman MI, Wilkinson M, Ambroggio L, Pang XL, Cauchemez S, Malley R, Klassen TP, Lee BE, Payne DC, Mahmud SM, Freedman SB. Household Transmission Dynamics of Asymptomatic SARS-CoV-2-Infected Children: A Multinational, Controlled Case-Ascertained Prospective Study. Clin Infect Dis 2024; 78:1522-1530. [PMID: 38530249 PMCID: PMC11175701 DOI: 10.1093/cid/ciae069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND Asymptomatic SARS-CoV-2 infection in children is highly prevalent but its acute and chronic implications have been minimally described. METHODS In this controlled case-ascertained household transmission study, we recruited asymptomatic children <18 years with SARS-CoV-2 nucleic acid testing performed at 12 tertiary care pediatric institutions in Canada and the United States. We attempted to recruit all test-positive children and 1 to 3 test-negative, site-matched controls. After 14 days' follow-up we assessed the clinical (ie, symptomatic) and combined (ie, test-positive, or symptomatic) secondary attack rates (SARs) among household contacts. Additionally, post-COVID-19 condition (PCC) was assessed in SARS-CoV-2-positive participating children after 90 days' follow-up. RESULTS A total of 111 test-positive and 256 SARS-CoV-2 test-negative asymptomatic children were enrolled between January 2021 and April 2022. After 14 days, excluding households with co-primary cases, the clinical SAR among household contacts of SARS-CoV-2-positive and -negative index children was 10.6% (19/179; 95% CI: 6.5%-16.1%) and 2.0% (13/663; 95% CI: 1.0%-3.3%), respectively (relative risk = 5.4; 95% CI: 2.7-10.7). In households with a SARS-CoV-2-positive index child, age <5 years, being pre-symptomatic (ie, developed symptoms after test), and testing positive during Omicron and Delta circulation periods (vs earlier) were associated with increased clinical and combined SARs among household contacts. Among 77 asymptomatic SARS-CoV-2-infected children with 90-day follow-up, 6 (7.8%; 95% CI: 2.9%-16.2%) reported PCC. CONCLUSIONS Asymptomatic SARS-CoV-2-infected children, especially those <5 years, are important contributors to household transmission, with 1 in 10 exposed household contacts developing symptomatic illness within 14 days. Asymptomatic SARS-CoV-2-infected children may develop PCC.
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Affiliation(s)
- Anna Funk
- Department of Obstetrics and Gynecology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Todd A Florin
- Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Division of Emergency Medicine, Ann and Robert H. Lurie Children's Hospital Chicago, Chicago, Illinois, USA
| | - Nathan Kuppermann
- Department of Emergency Medicine, University of California, Davis School of Medicine, Sacramento, California, USA
- Department of Pediatrics, University of California, Davis School of Medicine, Sacramento, California, USA
| | - Yaron Finkelstein
- Divisions of Emergency Medicine and Clinical Pharmacology and Toxicology, Department of Pediatrics, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Alissa Kazakoff
- Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada
| | - Michael Baldovsky
- Division of Pediatric Emergency Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Daniel J Tancredi
- Department of Pediatrics, University of California, Davis School of Medicine, Sacramento, California, USA
| | - Kristen Breslin
- Division of Emergency Medicine, Children's National Hospital, Washington, D.C., USA
| | - Kelly R Bergmann
- Department of Pediatric Emergency Medicine, Children's Minnesota, Minneapolis, Minnesota, USA
| | - Michael Gardiner
- Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California, USA
- Division of Emergency Medicine, Rady Children's Hospital, San Diego, California, USA
| | - Christopher M Pruitt
- Department of Pediatrics, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Deborah R Liu
- Division of Emergency Medicine, Department of Pediatrics, Children's Hospital Los Angeles, Keck USC School of Medicine, Los Angeles, California, USA
| | - Mark I Neuman
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
- Division of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Matthew Wilkinson
- Department of Pediatrics, University of Texas at Austin, Dell Medical School, Austin, Texas, USA
| | - Lilliam Ambroggio
- Department of Pediatrics, University of Colorado, Aurora, Colorado, USA
- Section of Emergency Medicine, Children's Hospital Colorado, Aurora, Colorado, USA
| | - Xiao-Li Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, CNRS UMR 2000, Paris, France
| | - Richard Malley
- Division of Infectious Diseases, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Terry P Klassen
- Children's Hospital Research Institute of Manitoba, University of Manitoba, Winnipeg, Manitoba, Canada
- Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Bonita E Lee
- Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada
| | - Daniel C Payne
- National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Salaheddin M Mahmud
- Dept of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Stephen B Freedman
- Section of Pediatric Emergency Medicine, Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Section of Gastroenterology, Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Emergency Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
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Mallela A, Chen Y, Lin YT, Miller EF, Neumann J, He Z, Nelson KE, Posner RG, Hlavacek WS. Impacts of Vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 Variants Alpha and Delta on Coronavirus Disease 2019 Transmission Dynamics in Four Metropolitan Areas of the United States. Bull Math Biol 2024; 86:31. [PMID: 38353870 DOI: 10.1007/s11538-024-01258-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 01/08/2024] [Indexed: 02/16/2024]
Abstract
To characterize Coronavirus Disease 2019 (COVID-19) transmission dynamics in each of the metropolitan statistical areas (MSAs) surrounding Dallas, Houston, New York City, and Phoenix in 2020 and 2021, we extended a previously reported compartmental model accounting for effects of multiple distinct periods of non-pharmaceutical interventions by adding consideration of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants Alpha (lineage B.1.1.7) and Delta (lineage B.1.617.2). For each MSA, we found region-specific parameterizations of the model using daily reports of new COVID-19 cases available from January 21, 2020 to October 31, 2021. In the process, we obtained estimates of the relative infectiousness of Alpha and Delta as well as their takeoff times in each MSA (the times at which sustained transmission began). The estimated infectiousness of Alpha ranged from 1.1x to 1.4x that of viral strains circulating in 2020 and early 2021. The estimated relative infectiousness of Delta was higher in all cases, ranging from 1.6x to 2.1x. The estimated Alpha takeoff times ranged from February 1 to February 28, 2021. The estimated Delta takeoff times ranged from June 2 to June 26, 2021. Estimated takeoff times are consistent with genomic surveillance data.
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Affiliation(s)
- Abhishek Mallela
- Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
| | - Ye Chen
- Department of Mathematics and Statistics, Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - Yen Ting Lin
- Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
- Information Sciences Group, Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
| | - Ely F Miller
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - Jacob Neumann
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - Zhili He
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - Kathryn E Nelson
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - Richard G Posner
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - William S Hlavacek
- Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA.
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA.
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Ji J, Viloria Winnett A, Shelby N, Reyes JA, Schlenker NW, Davich H, Caldera S, Tognazzini C, Goh YY, Feaster M, Ismagilov RF. Index cases first identified by nasal-swab rapid COVID-19 tests had more transmission to household contacts than cases identified by other test types. PLoS One 2023; 18:e0292389. [PMID: 37796850 PMCID: PMC10553276 DOI: 10.1371/journal.pone.0292389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 09/19/2023] [Indexed: 10/07/2023] Open
Abstract
At-home rapid COVID-19 tests in the U.S. utilize nasal-swab specimens and require high viral loads to reliably give positive results. Longitudinal studies from the onset of infection have found infectious virus can present in oral specimens days before nasal. Detection and initiation of infection-control practices may therefore be delayed when nasal-swab rapid tests are used, resulting in greater transmission to contacts. We assessed whether index cases first identified by rapid nasal-swab COVID-19 tests had more transmission to household contacts than index cases who used other test types (tests with higher analytical sensitivity and/or non-nasal specimen types). In this observational cohort study, 370 individuals from 85 households with a recent COVID-19 case were screened at least daily by RT-qPCR on one or more self-collected upper-respiratory specimen types. A two-level random intercept model was used to assess the association between the infection outcome of household contacts and each covariable (household size, race/ethnicity, age, vaccination status, viral variant, infection-control practices, and whether a rapid nasal-swab test was used to initially identify the household index case). Transmission was quantified by adjusted secondary attack rates (aSAR) and adjusted odds ratios (aOR). An aSAR of 53.6% (95% CI 38.8-68.3%) was observed among households where the index case first tested positive by a rapid nasal-swab COVID-19 test, which was significantly higher than the aSAR for households where the index case utilized another test type (27.2% 95% CI 19.5-35.0%, P = 0.003 pairwise comparisons of predictive margins). We observed an aOR of 4.90 (95% CI 1.65-14.56) for transmission to household contacts when a nasal-swab rapid test was used to identify the index case, compared to other test types. Use of nasal-swab rapid COVID-19 tests for initial detection of infection and initiation of infection control may be less effective at limiting transmission to household contacts than other test types.
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Affiliation(s)
- Jenny Ji
- California Institute of Technology, Pasadena, California, United States of America
| | - Alexander Viloria Winnett
- California Institute of Technology, Pasadena, California, United States of America
- University of California Los Angeles–California Institute of Technology Medical Scientist Training Program, Los Angeles, California, United States of America
| | - Natasha Shelby
- California Institute of Technology, Pasadena, California, United States of America
| | - Jessica A. Reyes
- California Institute of Technology, Pasadena, California, United States of America
| | - Noah W. Schlenker
- California Institute of Technology, Pasadena, California, United States of America
| | - Hannah Davich
- California Institute of Technology, Pasadena, California, United States of America
| | - Saharai Caldera
- California Institute of Technology, Pasadena, California, United States of America
| | - Colten Tognazzini
- Pasadena Public Health Department, Pasadena, California, United States of America
| | - Ying-Ying Goh
- Pasadena Public Health Department, Pasadena, California, United States of America
| | - Matt Feaster
- Pasadena Public Health Department, Pasadena, California, United States of America
| | - Rustem F. Ismagilov
- California Institute of Technology, Pasadena, California, United States of America
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Sun K, Loria V, Aparicio A, Porras C, Vanegas JC, Zúñiga M, Morera M, Avila C, Abdelnour A, Gail MH, Pfeiffer R, Cohen JI, Burbelo PD, Abed MA, Viboud C, Hildesheim A, Herrero R, Prevots DR. Behavioral factors and SARS-CoV-2 transmission heterogeneity within a household cohort in Costa Rica. COMMUNICATIONS MEDICINE 2023; 3:102. [PMID: 37481623 PMCID: PMC10363136 DOI: 10.1038/s43856-023-00325-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 06/21/2023] [Indexed: 07/24/2023] Open
Abstract
INTRODUCTION Variability in household secondary attack rates and transmission risks factors of SARS-CoV-2 remain poorly understood. METHODS We conducted a household transmission study of SARS-CoV-2 in Costa Rica, with SARS-CoV-2 index cases selected from a larger prospective cohort study and their household contacts were enrolled. A total of 719 household contacts of 304 household index cases were enrolled from November 21, 2020, through July 31, 2021. Blood specimens were collected from contacts within 30-60 days of index case diagnosis; and serum was tested for presence of spike and nucleocapsid SARS-CoV-2 IgG antibodies. Evidence of SARS-CoV-2 prior infections among household contacts was defined based on the presence of both spike and nucleocapsid antibodies. We fitted a chain binomial model to the serologic data, to account for exogenous community infection risk and potential multi-generational transmissions within the household. RESULTS Overall seroprevalence was 53% (95% confidence interval (CI) 48-58%) among household contacts. The estimated household secondary attack rate is 34% (95% CI 5-75%). Mask wearing by the index case is associated with the household transmission risk reduction by 67% (adjusted odds ratio = 0.33 with 95% CI: 0.09-0.75) and not sharing bedroom with the index case is associated with the risk reduction of household transmission by 78% (adjusted odds ratio = 0.22 with 95% CI 0.10-0.41). The estimated distribution of household secondary attack rates is highly heterogeneous across index cases, with 30% of index cases being the source for 80% of secondary cases. CONCLUSIONS Modeling analysis suggests that behavioral factors are important drivers of the observed SARS-CoV-2 transmission heterogeneity within the household.
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Affiliation(s)
- Kaiyuan Sun
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health (NIH), Bethesda, MD, USA.
| | - Viviana Loria
- Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica
| | - Amada Aparicio
- Caja Costarricense de Seguro Social, San José, Costa Rica
| | - Carolina Porras
- Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica
| | - Juan Carlos Vanegas
- Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica
| | - Michael Zúñiga
- Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica
| | - Melvin Morera
- Caja Costarricense de Seguro Social, San José, Costa Rica
| | - Carlos Avila
- Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica
| | | | - Mitchell H Gail
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Ruth Pfeiffer
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Jeffrey I Cohen
- Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda, MD, USA
| | - Peter D Burbelo
- National Institute of Dental and Craniofacial Research, NIH, Bethesda, MD, USA
| | - Mehdi A Abed
- National Institute of Dental and Craniofacial Research, NIH, Bethesda, MD, USA
| | - Cécile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Allan Hildesheim
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Rolando Herrero
- Agencia Costarricense de Investigaciones Biomédicas (ACIB) - Fundación INCIENSA (FUNIN), San José, Costa Rica
| | - D Rebecca Prevots
- Epidemiology and Population Studies Unit, Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, NIAID, NIH, Bethesda, MD, USA.
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Zhu Y, Xia Y, Pickering J, Bowen AC, Short KR. The role of children in transmission of SARS-CoV-2 variants of concern within households: an updated systematic review and meta-analysis, as at 30 June 2022. Euro Surveill 2023; 28:2200624. [PMID: 37140450 PMCID: PMC10161681 DOI: 10.2807/1560-7917.es.2023.28.18.2200624] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 03/17/2023] [Indexed: 05/05/2023] Open
Abstract
BackgroundMeta-analyses and single-site studies have established that children are less infectious than adults within a household when positive for ancestral SARS-CoV-2. In addition, children appear less susceptible to infection when exposed to ancestral SARS-CoV-2 within a household. The emergence of SARS-CoV-2 variants of concern (VOC) has been associated with an increased number of paediatric infections worldwide. However, the role of children in the household transmission of VOC, relative to the ancestral virus, remains unclear.AimWe aimed to evaluate children's role in household transmission of SARS-CoV-2 VOC.MethodsWe perform a meta-analysis of the role of children in household transmission of both ancestral SARS-CoV-2 and SARS-CoV-2 VOC.ResultsUnlike with the ancestral virus, children infected with VOC spread SARS-CoV-2 to an equivalent number of household contacts as infected adults and were equally as likely to acquire SARS-CoV-2 VOC from an infected family member. Interestingly, the same was observed when unvaccinated children exposed to VOC were compared with unvaccinated adults exposed to VOC.ConclusionsThese data suggest that the emergence of VOC was associated with a fundamental shift in the epidemiology of SARS-CoV-2. It is unlikely that this is solely the result of age-dependent differences in vaccination during the VOC period and may instead reflect virus evolution over the course of the pandemic.
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Affiliation(s)
- Yanshan Zhu
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
- Wesfarmer's Centre for Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Nedlands, Perth, Australia
- These authors contributed equally to this manuscript
| | - Yao Xia
- Department of Microbiology, State Key Laboratory of Emerging Infectious Diseases, Carol Yu Centre for Infection, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
- These authors contributed equally to this manuscript
| | - Janessa Pickering
- Wesfarmer's Centre for Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Nedlands, Perth, Australia
| | - Asha C Bowen
- Wesfarmer's Centre for Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Nedlands, Perth, Australia
- Department of Infectious Diseases, Perth Children's Hospital, Nedlands, Perth, Australia
| | - Kirsty R Short
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
- Australian Infectious Diseases Research Centre, The University of Queensland, Brisbane, Australia
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Gulley C, Kepler KL, Ngai S, Waechter H, Fitzhenry R, Thompson CN, Fine A, Reddy V. Clustering of SARS-CoV-2 in Households in New York City: A Building-Level Analysis, March-December 2020. JOURNAL OF PUBLIC HEALTH MANAGEMENT AND PRACTICE 2023; 29:587-595. [PMID: 36943404 DOI: 10.1097/phh.0000000000001728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
OBJECTIVES To identify the proportion of coronavirus disease 2019 (COVID-19) cases that occurred within households or buildings in New York City (NYC) beginning in March 2020 during the first stay-at-home order to determine transmission attributable to these settings and inform targeted prevention strategies. DESIGN The residential addresses of cases were geocoded (converting descriptive addresses to latitude and longitude coordinates) and used to identify clusters of cases residing in unique buildings based on building identification number (BIN), a unique building identifier. Household clusters were defined as 2 or more cases within 2 weeks of onset or diagnosis date in the same BIN with the same unit number, last name, or in a single-family home. Building clusters were defined as 3 or more cases with onset date or diagnosis date within 2 weeks in the same BIN who do not reside in the same household. SETTING NYC from March to December 2020. PARTICIPANTS NYC residents with a positive SARS-CoV-2 nucleic acid amplification or antigen test result with a specimen collected during March 1, 2020, to December 31, 2020. MAIN OUTCOME MEASURE The proportion of NYC COVID-19 cases in a household or building cluster. RESULTS The BIN analysis identified 65 343 building and household clusters: 17 139 (26%) building clusters and 48 204 (74%) household clusters. A substantial proportion of NYC COVID-19 cases (43%) were potentially attributable to household transmission in the first 9 months of the pandemic. CONCLUSIONS Geocoded address matching assisted in identifying COVID-19 household clusters. Close contact transmission within a household or building cluster was found in 43% of noncongregate cases with a valid residential NYC address. The BIN analysis should be utilized to identify disease clustering for improved surveillance.
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Affiliation(s)
- Catherine Gulley
- New York City Department of Health and Mental Hygiene, Queens, New York. Ms Gulley is now with JBS International, Rockville, Maryland
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Wang C, Huang X, Lau EHY, Cowling BJ, Tsang TK. Association Between Population-Level Factors and Household Secondary Attack Rate of SARS-CoV-2: A Systematic Review and Meta-analysis. Open Forum Infect Dis 2022; 10:ofac676. [PMID: 36655186 PMCID: PMC9835764 DOI: 10.1093/ofid/ofac676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 12/14/2022] [Indexed: 12/23/2022] Open
Abstract
Background Accurate estimation of household secondary attack rate (SAR) is crucial to understand the transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The impact of population-level factors, such as transmission intensity in the community, on SAR estimates is rarely explored. Methods In this study, we included articles with original data to compute the household SAR. To determine the impact of transmission intensity in the community on household SAR estimates, we explored the association between SAR estimates and the incidence rate of cases by country during the study period. Results We identified 163 studies to extract data on SARs from 326 031 cases and 2 009 859 household contacts. The correlation between the incidence rate of cases during the study period and SAR estimates was 0.37 (95% CI, 0.24-0.49). We found that doubling the incidence rate of cases during the study period was associated with a 1.2% (95% CI, 0.5%-1.8%) higher household SAR. Conclusions Our findings suggest that the incidence rate of cases during the study period is associated with higher SAR. Ignoring this factor may overestimate SARs, especially for regions with high incidences, which further impacts control policies and epidemiological characterization of emerging variants.
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Affiliation(s)
- Can Wang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Xiaotong Huang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Eric H Y Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China,Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China,Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China
| | - Tim K Tsang
- Correspondence: Tim K. Tsang, PhD, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong Special Administrative Region, China ()
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Della Polla G, Miraglia del Giudice G, Folcarelli L, Napoli A, Angelillo IF. Willingness to accept a second COVID-19 vaccination booster dose among healthcare workers in Italy. Front Public Health 2022; 10:1051035. [PMID: 36568799 PMCID: PMC9780496 DOI: 10.3389/fpubh.2022.1051035] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 11/10/2022] [Indexed: 12/14/2022] Open
Abstract
Background The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is evolving,the newly emerged Omicron variant being the dominant strain worldwide, and this has raised concerns about vaccine efficacy. The purposes of this survey were to examine the extent to which healthcare workers (HCWs) intend to receive a second booster dose of the COVID-19 vaccine and the factors that influence their willingness to accept it. Methods The study was conducted among HCWs who were randomly selected from four public hospitals in the Campania region, Southern Italy. Results A total of 496 HCWs answered the questionnaire (a response rate of 61.2%). Among the respondents, 20.8% indicated a score of 10, using a 10-point Likert-type scale, regarding the usefulness of a second COVID-19 vaccine booster dose. Physicians, HCWs who believed that COVID-19 was a severe disease, and those who have acquired information about the second booster dose from scientific journals were more likely to have this positive attitude. Slightly more than half of HCWs self-reported willingness to receive a second booster dose. Respondents who believe that HCWs are at higher risk of being infected by SARS-CoV-2, those who have a higher belief that COVID-19 is a severe disease, and those who have a higher belief that a second booster dose is useful were more willing to receive a second booster dose. The main reasons for those who had a positive intention were to protect their family members and patients, whereas, the main reasons for not getting vaccinated or for uncertainty were that the dose does not offer protection against the emerging variants and the fear of its side effects. HCWs of younger age, physicians, those who have a higher belief that a second booster dose is useful, and those who were willing to receive a second booster dose were more likely to recommend the booster dose to their patients. Conclusion This study's findings highlight the necessity for designing and implementing educational interventions for improving second booster dose uptake and beliefs among HCWs and their capacity to recommend the vaccine to the patients.
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Affiliation(s)
- Giorgia Della Polla
- Department of Public Health and Laboratory Services, Teaching Hospital, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | | | - Lucio Folcarelli
- Department of Experimental Medicine, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Annalisa Napoli
- Department of Experimental Medicine, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Italo Francesco Angelillo
- Department of Public Health and Laboratory Services, Teaching Hospital, University of Campania “Luigi Vanvitelli”, Naples, Italy,Department of Experimental Medicine, University of Campania “Luigi Vanvitelli”, Naples, Italy,*Correspondence: Italo Francesco Angelillo
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Shragai T, Pratt C, Castro Georgi J, Donnelly MAP, Schwartz NG, Soto R, Chuey M, Chu VT, Marcenac P, Park GW, Ahmad A, Albanese B, Totten SE, Austin B, Bunkley P, Cherney B, Dietrich EA, Figueroa E, Folster JM, Godino C, Herzegh O, Lindell K, Relja B, Sheldon SW, Tong S, Vinjé J, Thornburg NJ, Matanock AM, Hughes LJ, Stringer G, Hudziec M, Beatty ME, Tate JE, Kirking HL, Hsu CH. Household characteristics associated with surface contamination of SARS-CoV-2 and frequency of RT-PCR and viral culture positivity-California and Colorado, 2021. PLoS One 2022; 17:e0274946. [PMID: 36215247 PMCID: PMC9550039 DOI: 10.1371/journal.pone.0274946] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 09/07/2022] [Indexed: 11/18/2022] Open
Abstract
While risk of fomite transmission of SARS-CoV-2 is considered low, there is limited environmental data within households. This January-April 2021 investigation describes frequency and types of surfaces positive for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (RT-PCR) among residences with ≥1 SARS-CoV-2 infection, and associations of household characteristics with surface RT-PCR and viable virus positivity. Of 1232 samples from 124 households, 27.8% (n = 342) were RT-PCR positive with nightstands (44.1%) and pillows (40.9%) most frequently positive. SARS-CoV-2 lineage, documented household transmission, greater number of infected persons, shorter interval between illness onset and sampling, total household symptoms, proportion of infected persons ≤12 years old, and persons exhibiting upper respiratory symptoms or diarrhea were associated with more positive surfaces. Viable virus was isolated from 0.2% (n = 3 samples from one household) of all samples. This investigation suggests that while SARS-CoV-2 on surfaces is common, fomite transmission risk in households is low.
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Affiliation(s)
- Talya Shragai
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Caroline Pratt
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
- * E-mail:
| | | | - Marisa A. P. Donnelly
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Noah G. Schwartz
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Raymond Soto
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Meagan Chuey
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Victoria T. Chu
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Perrine Marcenac
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Geun Woo Park
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Ausaf Ahmad
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Bernadette Albanese
- Tri-County Health Department, Adams, Arapahoe, and Douglas Counties, Colorado, United States of America
| | - Sarah Elizabeth Totten
- Colorado Department of Public Health and Environment, Glendale, Colorado, United States of America
| | - Brett Austin
- Health and Human Services, San Diego County, California, United States of America
| | - Paige Bunkley
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Blake Cherney
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Elizabeth A. Dietrich
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Erica Figueroa
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Jennifer M. Folster
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Claire Godino
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Owen Herzegh
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Kristine Lindell
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Boris Relja
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Sarah W. Sheldon
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Suxiang Tong
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Jan Vinjé
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Natalie J. Thornburg
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Almea M. Matanock
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Laura J. Hughes
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Ginger Stringer
- Colorado Department of Public Health and Environment, Glendale, Colorado, United States of America
| | - Meghan Hudziec
- Colorado Department of Public Health and Environment, Glendale, Colorado, United States of America
| | - Mark E. Beatty
- Health and Human Services, San Diego County, California, United States of America
| | - Jacqueline E. Tate
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Hannah L. Kirking
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Christopher H. Hsu
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
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10
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Chen F, Tian Y, Zhang L, Shi Y. The role of children in household transmission of COVID-19: a systematic review and meta-analysis. Int J Infect Dis 2022; 122:266-275. [PMID: 35562045 PMCID: PMC9091150 DOI: 10.1016/j.ijid.2022.05.016] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/03/2022] [Accepted: 05/07/2022] [Indexed: 02/08/2023] Open
Abstract
OBJECTIVES To explore household transmissibility of SARS-CoV-2 in children in new-variants dominating periods. METHODS Through retrieval in PubMed and Embase, studies were included in two parts: meta-analysis of the household secondary attack rate (SAR) and case analysis of household pediatric infections. RESULTS A total of 95 articles were included: 48 for meta-analysis and 47 for case analysis. Pediatric COVID-19 only comprised a minority of the household transmission. The total pooled household SAR of child index cases and contacts were 0.20 (95% confidence interval [CI]: 0.15-0.26) and 0.24 (95% CI: 0.18-0.30). Lower household transmissibility was reported in both child index cases and contacts than in adults (relative risk [RR] = 0.64, 95% CI: 0.50-0.81; RR = 0.74, 95% CI: 0.64-0.85). Younger children were as susceptible as the older children (RR = 0.89, 95% CI: 0.72-1.10). Through subgroup analyses of different variants and periods, increased household SAR was observed in children (Wild: 0.20; Alpha: 0.42; Delta: 0.35; Omicron: 0.56), and no significant difference was found in household SAR between children and adults when new variants dominated. CONCLUSION Although children were found not to be dominant in the household transmission, their transmissibility of SARS-CoV-2 appeared to be on the rise as new variants emerged.
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Affiliation(s)
| | | | | | - Yuan Shi
- Corresponding author: Yuan Shi, Children's Hospital of Chongqing Medical University, Chongqing 400014, China, Mob: 00862363635678
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11
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McCormick DW, Konkle SL, Magleby R, Chakrabarti AK, Cherney B, Lindell K, Namageyo-Funa A, Visser S, Soto RA, Donnelly MAP, Stringer G, Austin B, Beatty ME, Stous S, Albanese BA, Chu VT, Chuey M, Dietrich EA, Drobeniuc J, Folster JM, Killerby ME, Lehman JA, McDonald EC, Ruffin J, Schwartz NG, Sheldon SW, Sleweon S, Thornburg NJ, Hughes LJ, Petway M, Tong S, Whaley MJ, Kirking HL, Tate JE, Hsu CH, Matanock A. SARS-CoV-2 infection risk among vaccinated and unvaccinated household members during the Alpha variant surge - Denver, Colorado, and San Diego, California, January-April 2021. Vaccine 2022; 40:4845-4855. [PMID: 35803846 PMCID: PMC9250903 DOI: 10.1016/j.vaccine.2022.06.066] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 06/17/2022] [Accepted: 06/18/2022] [Indexed: 11/04/2022]
Abstract
BACKGROUND COVID-19 vaccination reduces SARS-CoV-2 infection and transmission. However, evidence is emerging on the degree of protection across variants and in high-transmission settings. To better understand the protection afforded by vaccination specifically in a high-transmission setting, we examined household transmission of SARS-CoV-2 during a period of high community incidence with predominant SARS-CoV-2 B.1.1.7 (Alpha) variant, among vaccinated and unvaccinated contacts. METHODS We conducted a household transmission investigation in San Diego County, California, and Denver, Colorado, during January-April 2021. Households were enrolled if they had at least one person with documented SARS-CoV-2 infection. We collected nasopharyngeal swabs, blood, demographic information, and vaccination history from all consenting household members. We compared infection risks (IRs), RT-PCR cycle threshold values, SARS-CoV-2 culture results, and antibody statuses among vaccinated and unvaccinated household contacts. RESULTS We enrolled 493 individuals from 138 households. The SARS-CoV-2 variant was identified from 121/138 households (88%). The most common variants were Alpha (75/121, 62%) and Epsilon (19/121, 16%). There were no households with discordant lineages among household members. One fully vaccinated secondary case was symptomatic (13%); the other 5 were asymptomatic (87%). Among unvaccinated secondary cases, 105/108 (97%) were symptomatic. Among 127 households with a single primary case, the IR for household contacts was 45% (146/322; 95% Confidence Interval [CI] 40-51%). The observed IR was higher in unvaccinated (130/257, 49%, 95% CI 45-57%) than fully vaccinated contacts (6/26, 23%, 95% CI 11-42%). A lower proportion of households with a fully vaccinated primary case had secondary cases (1/5, 20%) than households with an unvaccinated primary case (66/108, 62%). CONCLUSIONS Although SARS-CoV-2 infections in vaccinated household contacts were reported in this high transmission setting, full vaccination protected against SARS-CoV-2 infection. These findings further support the protective effect of COVID-19 vaccination and highlight the need for ongoing vaccination among eligible persons.
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Affiliation(s)
- David W McCormick
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Stacey L Konkle
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Reed Magleby
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ayan K Chakrabarti
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Blake Cherney
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Kristine Lindell
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Apophia Namageyo-Funa
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Susanna Visser
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Raymond A Soto
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Marisa A P Donnelly
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ginger Stringer
- Colorado Department of Public Health and the Environment, Denver, CO, USA
| | - Brett Austin
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Mark E Beatty
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Sarah Stous
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | | | - Victoria T Chu
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Meagan Chuey
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA; County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Elizabeth A Dietrich
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jan Drobeniuc
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jennifer M Folster
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Marie E Killerby
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jennifer A Lehman
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Eric C McDonald
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Jasmine Ruffin
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Noah G Schwartz
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sarah W Sheldon
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sadia Sleweon
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Natalie J Thornburg
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Laura J Hughes
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Marla Petway
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Suxiang Tong
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Melissa J Whaley
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Hannah L Kirking
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jacqueline E Tate
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Christopher H Hsu
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Almea Matanock
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
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12
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Waltenburg MA, Whaley MJ, Chancey RJ, Donnelly MA, Chuey MR, Soto R, Schwartz NG, Chu VT, Sleweon S, McCormick DW, Uehara A, Retchless AC, Tong S, Folster JM, Petway M, Thornburg NJ, Drobeniuc J, Austin B, Hudziec MM, Stringer G, Albanese BA, Totten SE, Matzinger SR, Staples JE, Killerby ME, Hughes LJ, Matanock A, Beatty M, Tate JE, Kirking HL, Hsu CH. Household Transmission and Symptomology of Severe Acute Respiratory Syndrome Coronavirus 2 Alpha Variant among Children-California and Colorado, 2021. J Pediatr 2022; 247:29-37.e7. [PMID: 35447121 PMCID: PMC9015725 DOI: 10.1016/j.jpeds.2022.04.032] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/30/2022] [Accepted: 04/15/2022] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To assess the household secondary infection risk (SIR) of B.1.1.7 (Alpha) and non-Alpha lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among children. STUDY DESIGN During January to April 2021, we prospectively followed households with a SARS-CoV-2 infection. We collected questionnaires, serial nasopharyngeal swabs for reverse transcription polymerase chain reaction testing and whole genome sequencing, and serial blood samples for serology testing. We calculated SIRs by primary case age (pediatric vs adult), household contact age, and viral lineage. We evaluated risk factors associated with transmission and described symptom profiles among children. RESULTS Among 36 households with pediatric primary cases, 21 (58%) had secondary infections. Among 91 households with adult primary cases, 51 (56%) had secondary infections. SIRs among pediatric and adult primary cases were 45% and 54%, respectively (OR, 0.79; 95% CI, 0.41-1.54). SIRs among pediatric primary cases with Alpha and non-Alpha lineage were 55% and 46%, respectively (OR, 1.52; 95% CI, 0.51-4.53). SIRs among pediatric and adult household contacts were 55% and 49%, respectively (OR, 1.01; 95% CI, 0.68-1.50). Among pediatric contacts, no significant differences in the odds of acquiring infection by demographic or household characteristics were observed. CONCLUSIONS Household transmission of SARS-CoV-2 from children and adult primary cases to household members was frequent. The risk of secondary infection was similar among child and adult household contacts. Among children, household transmission of SARS-CoV-2 and the risk of secondary infection was not influenced by lineage. Continued mitigation strategies (eg, masking, physical distancing, vaccination) are needed to protect at-risk groups regardless of virus lineage circulating in communities.
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Affiliation(s)
- Michelle A. Waltenburg
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA,Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA,Reprint requests: Michelle A. Waltenburg, DVM, MPH, Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA 30329
| | - Melissa J. Whaley
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Rebecca J. Chancey
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Marisa A.P. Donnelly
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA,Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA
| | - Meagan R. Chuey
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA,County of San Diego Health and Human Services Agency, San Diego, CA
| | - Raymond Soto
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA,Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA
| | - Noah G. Schwartz
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA,Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA
| | - Victoria T. Chu
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA,Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA
| | - Sadia Sleweon
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - David W. McCormick
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA,Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA
| | - Anna Uehara
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Adam C. Retchless
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Suxiang Tong
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Jennifer M. Folster
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Marla Petway
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Natalie J. Thornburg
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Jan Drobeniuc
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Brett Austin
- County of San Diego Health and Human Services Agency, San Diego, CA
| | | | - Ginger Stringer
- Colorado Department of Public Health and Environment, Denver, CO
| | | | - Sarah E. Totten
- Colorado Department of Public Health and Environment, Denver, CO
| | | | - J. Erin Staples
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Marie E. Killerby
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Laura J. Hughes
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Almea Matanock
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Mark Beatty
- County of San Diego Health and Human Services Agency, San Diego, CA
| | - Jacqueline E. Tate
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Hannah L. Kirking
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
| | - Christopher H. Hsu
- Coronavirus Disease 2019 Response Team, Centers for Disease Control and Prevention, Atlanta, GA
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13
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Jacobsen H, Cobos Jiménez V, Sitaras I, Bar-Zeev N, Čičin-Šain L, Higdon MM, Deloria-Knoll M. Post-vaccination T cell immunity to omicron. Front Immunol 2022; 13:944713. [PMID: 35990661 PMCID: PMC9386871 DOI: 10.3389/fimmu.2022.944713] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 06/30/2022] [Indexed: 11/13/2022] Open
Abstract
In late 2021, the omicron variant of SARS Coronavirus 2 (SARS-CoV-2) emerged and replaced the previously dominant delta strain. Effectiveness of COVID-19 vaccines against omicron has been challenging to estimate in clinical studies or is not available for all vaccines or populations of interest. T cell function can be predictive of vaccine longevity and effectiveness against disease, likely in a more robust way than antibody neutralization. In this mini review, we summarize the evidence on T cell immunity against omicron including effects of boosters, homologous versus heterologous regimens, hybrid immunity, memory responses and vaccine product. Overall, T cell reactivity in post-vaccine specimens is largely preserved against omicron, indicating that vaccines utilizing the parental antigen continue to be protective against disease caused by the omicron variant.
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Affiliation(s)
- Henning Jacobsen
- Department of Viral Immunology, Helmholtz Center for Infection Research, Braunschweig, Germany
- *Correspondence: Henning Jacobsen,
| | - Viviana Cobos Jiménez
- Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, MD, United States
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States
| | - Ioannis Sitaras
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Naor Bar-Zeev
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Luka Čičin-Šain
- Department of Viral Immunology, Helmholtz Center for Infection Research, Braunschweig, Germany
- Centre for Individualised Infection Medicine (CIIM), a joint venture of HZI and MHH, Hannover, Germany
- German Centre for Infection Research (DZIF), Hannover-Braunschweig site, Germany
| | - Melissa M. Higdon
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Maria Deloria-Knoll
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
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14
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Chu VT, Schwartz NG, Donnelly MAP, Chuey MR, Soto R, Yousaf AR, Schmitt-Matzen EN, Sleweon S, Ruffin J, Thornburg N, Harcourt JL, Tamin A, Kim G, Folster JM, Hughes LJ, Tong S, Stringer G, Albanese BA, Totten SE, Hudziec MM, Matzinger SR, Dietrich EA, Sheldon SW, Stous S, McDonald EC, Austin B, Beatty ME, Staples JE, Killerby ME, Hsu CH, Tate JE, Kirking HL, Matanock A. Comparison of Home Antigen Testing With RT-PCR and Viral Culture During the Course of SARS-CoV-2 Infection. JAMA Intern Med 2022; 182:701-709. [PMID: 35486394 PMCID: PMC9055515 DOI: 10.1001/jamainternmed.2022.1827] [Citation(s) in RCA: 70] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
IMPORTANCE As self-collected home antigen tests become widely available, a better understanding of their performance during the course of SARS-CoV-2 infection is needed. OBJECTIVE To evaluate the diagnostic performance of home antigen tests compared with reverse transcription-polymerase chain reaction (RT-PCR) and viral culture by days from illness onset, as well as user acceptability. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study was conducted from January to May 2021 in San Diego County, California, and metropolitan Denver, Colorado. The convenience sample included adults and children with RT-PCR-confirmed infection who used self-collected home antigen tests for 15 days and underwent at least 1 nasopharyngeal swab for RT-PCR, viral culture, and sequencing. EXPOSURES SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURES The primary outcome was the daily sensitivity of home antigen tests to detect RT-PCR-confirmed cases. Secondary outcomes included the daily percentage of antigen test, RT-PCR, and viral culture results that were positive, and antigen test sensitivity compared with same-day RT-PCR and cultures. Antigen test use errors and acceptability were assessed for a subset of participants. RESULTS This study enrolled 225 persons with RT-PCR-confirmed infection (median [range] age, 29 [1-83] years; 117 female participants [52%]; 10 [4%] Asian, 6 [3%] Black or African American, 50 [22%] Hispanic or Latino, 3 [1%] Native Hawaiian or Other Pacific Islander, 145 [64%] White, and 11 [5%] multiracial individuals) who completed 3044 antigen tests and 642 nasopharyngeal swabs. Antigen test sensitivity was 50% (95% CI, 45%-55%) during the infectious period, 64% (95% CI, 56%-70%) compared with same-day RT-PCR, and 84% (95% CI, 75%-90%) compared with same-day cultures. Antigen test sensitivity peaked 4 days after illness onset at 77% (95% CI, 69%-83%). Antigen test sensitivity improved with a second antigen test 1 to 2 days later, particularly early in the infection. Six days after illness onset, antigen test result positivity was 61% (95% CI, 53%-68%). Almost all (216 [96%]) surveyed individuals reported that they would be more likely to get tested for SARS-CoV-2 infection if home antigen tests were available over the counter. CONCLUSIONS AND RELEVANCE The results of this cohort study of home antigen tests suggest that sensitivity for SARS-CoV-2 was moderate compared with RT-PCR and high compared with viral culture. The results also suggest that symptomatic individuals with an initial negative home antigen test result for SARS-CoV-2 infection should test again 1 to 2 days later because test sensitivity peaked several days after illness onset and improved with repeated testing.
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Affiliation(s)
- Victoria T Chu
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia.,Epidemic Intelligence Service, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Noah G Schwartz
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia.,Epidemic Intelligence Service, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Marisa A P Donnelly
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia.,Epidemic Intelligence Service, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Meagan R Chuey
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia.,Epidemic Intelligence Service, US Centers for Disease Control and Prevention, Atlanta, Georgia.,County of San Diego Health and Human Services Agency, San Diego, California
| | - Raymond Soto
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia.,Epidemic Intelligence Service, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Anna R Yousaf
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia.,Epidemic Intelligence Service, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Emily N Schmitt-Matzen
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia.,Epidemic Intelligence Service, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Sadia Sleweon
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jasmine Ruffin
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Natalie Thornburg
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jennifer L Harcourt
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Azaibi Tamin
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Gimin Kim
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jennifer M Folster
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Laura J Hughes
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Suxiang Tong
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Ginger Stringer
- Colorado Department of Public Health and Environment, Denver
| | | | - Sarah E Totten
- Colorado Department of Public Health and Environment, Denver
| | | | | | - Elizabeth A Dietrich
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Sarah W Sheldon
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Sarah Stous
- County of San Diego Health and Human Services Agency, San Diego, California
| | - Eric C McDonald
- County of San Diego Health and Human Services Agency, San Diego, California
| | - Brett Austin
- County of San Diego Health and Human Services Agency, San Diego, California
| | - Mark E Beatty
- County of San Diego Health and Human Services Agency, San Diego, California
| | - J Erin Staples
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Marie E Killerby
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Christopher H Hsu
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jacqueline E Tate
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Hannah L Kirking
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Almea Matanock
- COVID-19 Response Team, US Centers for Disease Control and Prevention, Atlanta, Georgia
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15
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Li D, Li AE, Li ZQ, Bao Y, Liu T, Qin XR, Yu XJ. SARS-CoV-2 Delta Variant in Jingmen City, Hubei Province, China, 2021: Children Susceptible and Vaccination Breakthrough Infection. Front Microbiol 2022; 13:856757. [PMID: 35495649 PMCID: PMC9043846 DOI: 10.3389/fmicb.2022.856757] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 03/14/2022] [Indexed: 12/20/2022] Open
Abstract
Background The delta variant (B.1.617.2) of SARS-CoV-2 was the dominant viral strain causing COVID-19 in China, 2021. We reported a SARS-CoV-2 delta variant outbreak in Jingmen City, Hubei Province, China. Methods The data of epidemiological, clinical, laboratorial, and vaccination of COVID-19 cases were collected through field investigation and analyzed. Results During the outbreak from 4 to 20 August 2021, 58 cases of the SARS-CoV-2 delta variant (B.1.617.2) were identified with 15 (25.9%) asymptomatic and 43 (74.1%) symptomatic (mild and moderate) patients. The mean serial interval was 2.6 days (standard deviation: 2.0, 95% CI: 1.9-3.6). The median age of the patients was 39 years (ranging from 1 to 60 years) with the high proportion in children (19.0%). The secondary attack rate was 9.8% higher from parents to their children (<18 years) (46.2%, 95% CI: 14.8-77.5%) than that between spouses (36.4%, 95% CI: 14.5-58.2%), but no significant difference was observed (p > 0.05). Approximately half (27; 46.6%) of cases were vaccine breakthrough infections. In vaccine breakthrough cases (fully vaccinated), viral loads decreased 1.9-3.4-folds (p < 0.05), duration of viral shedding shortened 5 days (p < 0.05), and the risk of becoming symptomatic from asymptomatic decreased 33% (95% CI: 5-53%) (aged ≥12 years) than those in unvaccinated infections. Conclusions Children are highly susceptible to the SARS-CoV-2 delta variant in the COVID-19 outbreak in Jingmen City in 2021. Inactivated vaccine derived from wide-type strain can effectively reduce the viral load, duration of viral shedding, and clinical severity in vaccine breakthrough cases. Our study indicates that protective measures that include full vaccination against COVID-19, especially in children, should be strengthened.
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Affiliation(s)
- Dan Li
- State Key Laboratory of Virology, School of Public Health, Wuhan University, Wuhan, China
| | - Ai-E Li
- Jingmen Municipal Health Commission, Jingmen, China
| | - Zhu-Qing Li
- Jingmen Center for Disease Control and Prevention, Jingmen, China
| | - Yu Bao
- Jingmen Center for Disease Control and Prevention, Jingmen, China
| | - Tian Liu
- Jingzhou Center for Disease Control and Prevention, Jingzhou, China
| | - Xiang-Rong Qin
- Department of Clinical Laboratory, The Second Hospital of Shandong University, Jinan, China
| | - Xue-Jie Yu
- State Key Laboratory of Virology, School of Public Health, Wuhan University, Wuhan, China
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